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156 Results

Covariates Hiding in the Tails

Staff Working Paper 2021-45 Milian Bachem, Lerby Ergun, Casper G. de Vries
We characterize the bias in cross-sectional Hill estimates caused by common underlying factors and propose two simple-to-implement remedies. To test for the presence, direction and size of the bias, we use monthly US stock returns and annual US Census county population data.
Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods JEL Code(s): C, C0, C01, C1, C14, C5, C58

Payment Habits During COVID-19: Evidence from High-Frequency Transaction Data

Staff Working Paper 2021-43 Tatjana Dahlhaus, Angelika Welte
We examine how consumers have adjusted their payment habits during the COVID-19 pandemic. They seem to perform fewer transactions, spend more in each transaction, use less cash at the point of sale and withdraw cash from ATMs linked to their financial institution more often than from other ATMs.

Estimating Large-Dimensional Connectedness Tables: The Great Moderation Through the Lens of Sectoral Spillovers

Staff Working Paper 2021-37 Felix Brunner, Ruben Hipp
Understanding the size of sectoral links is crucial to predicting the impact of a crisis on the whole economy. We show that statistical learning techniques substantially outperform traditional estimation techniques when measuring large networks of these links.

Shaping the future: Policy shocks and the GDP growth distribution

Can central bank and government policies impact the risks around the outlook for GDP growth? We find that fiscal stimulus makes strong GDP growth more likely—even more so when monetary policy is constrained—rather than weak GDP growth less likely. Thus, fiscal stimulus should accelerate the recovery phase of the COVID-19 pandemic.

Detecting exuberance in house prices across Canadian cities

Staff Analytical Note 2021-9 Ugochi Emenogu, Cars Hommes, Mikael Khan
We introduce a model to detect periods of extrapolative house price expectations across Canadian cities. The House Price Exuberance Indicator can be updated on a quarterly basis to support the Bank of Canada’s broader assessment of housing market imbalances.

Networking the Yield Curve: Implications for Monetary Policy

We study how different monetary policies affect the yield curve and interact. Our study highlights the importance of the spillover structure across the yield curve for policy-making.

Using Payments Data to Nowcast Macroeconomic Variables During the Onset of COVID-19

Staff Working Paper 2021-2 James Chapman, Ajit Desai
We use retail payment data in conjunction with machine learning techniques to predict the effects of COVID-19 on the Canadian economy in near-real time. Our model yields a significant increase in macroeconomic prediction accuracy over a linear benchmark model.

Strategic Uncertainty in Financial Markets: Evidence from a Consensus Pricing Service

Staff Working Paper 2020-55 Lerby Ergun, Andreas Uthemann
We look at the informational content of consensus pricing in opaque over-the-counter markets. We show that the availability of price data informs participants mainly about other participants’ valuations, rather than about the value of a financial security.

On Causal Networks of Financial Firms: Structural Identification via Non-parametric Heteroskedasticity

Staff Working Paper 2020-42 Ruben Hipp
Banks’ business interactions create a network of relationships that are hidden in the correlations of bank stock returns. But for policy interventions, we need causality to understand how the network changes. Thus, this paper looks for the causal network anticipated by investors.

The New Benchmark for Forecasts of the Real Price of Crude Oil

How can we assess the quality of a forecast? We propose a new benchmark to evaluate forecasts of temporally aggregated series and show that the real price of oil is more difficult to predict than we thought.
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